Remote Sensing Image Classification in R

This book offers an introduction to remotely sensed image processing and classification in R using machine learning algorithms. It also provides a concise and practical reference tutorial, which equips readers to immediately start using the software platform and R packages for image processing and c...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Kamusoko, Courage (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Σειρά:Springer Geography,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Remote Sensing Image Classification in R  |h [electronic resource] /  |c by Courage Kamusoko. 
250 |a 1st ed. 2019. 
264 1 |a Singapore :  |b Springer Singapore :  |b Imprint: Springer,  |c 2019. 
300 |a XVIII, 189 p. 359 illus., 53 illus. in color.  |b online resource. 
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505 0 |a Dedication -- Preface -- Acknowledgements -- Acronyms and Abbreviations -- Chapter 1. Remote sensing Digital Image Processing in R -- Chapter 2. Pre-processing -- Chapter 3. Image Transformation,etc. 
520 |a This book offers an introduction to remotely sensed image processing and classification in R using machine learning algorithms. It also provides a concise and practical reference tutorial, which equips readers to immediately start using the software platform and R packages for image processing and classification. This book is divided into five chapters. Chapter 1 introduces remote sensing digital image processing in R, while chapter 2 covers pre-processing. Chapter 3 focuses on image transformation, and chapter 4 addresses image classification. Lastly, chapter 5 deals with improving image classification. R is advantageous in that it is open source software, available free of charge and includes several useful features that are not available in commercial software packages. This book benefits all undergraduate and graduate students, researchers, university teachers and other remote- sensing practitioners interested in the practical implementation of remote sensing in R. 
650 0 |a Remote sensing. 
650 0 |a Environmental geography. 
650 0 |a Computer programming. 
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